1. Technical Field
The invention relates to the measurement of tissue properties. More particularly the invention relates to the measurement of skin thickness based on near-infrared absorbance spectra.
2. Description of the Prior Art
Near infrared (NIR) tissue spectroscopy is a promising noninvasive technology that bases measurements on the irradiation of a tissue site with NIR energy in the 700-2500 nm wavelength range. The energy is focused onto an area of the skin and propagates according to the scattering and absorbance properties of the skin tissue. Thus, energy that is reflected by the skin or that is transmitted through the skin is detected provides information about the tissue volume encountered. Specifically, the attenuation of the light energy at each wavelength is a function of the structural properties and chemical composition of the tissue. Tissue layers, each containing a unique heterogeneous particulate distribution, affect light absorbance through scattering. Chemical components such as water, protein, fat and blood analytes absorb light proportionally to their concentration through unique absorbance profiles or signatures. The measurement of tissue properties, characteristics or composition is based on the technique of detecting the magnitude of light attenuation resulting from its respective scattering and/or absorbance properties.
Blood Analyte Prediction
While noninvasive prediction of blood analytes, such as blood glucose concentration, has been pursued through NIR spectroscopy, the reported success and product viability has been limited by the lack of a system for compensating for variations between individuals that produce dramatic changes in the optical properties of the tissue sample. For example, see O. Khalil Spectroscopic and clinical aspects of non-invasive glucose measurement, Clin Chem vol. 45, pp.165-77 (1999); or J. Roe, B. Smoller. Bloodless Glucose Measurements, Critical Reviews in Therapeutic Drug Carrier Systems, vol. 15, no. 3, pp. 199-241, (1998). These variations are related to structural differences in the irradiated tissue sample between individuals and include, for example, the thickness of the dermis, distribution and density of skin collagen and percent body fat. While the absorbance features caused by structural variation are repeatable by subject, over a population of subjects they produce confounding nonlinear spectral variation. See C. Tan, B. Statham, R. Marks and P. Payne. Skin thickness measurement by pulsed ultrasound: its reproducibility, validation and variability, British Journal of Dermatology, vol. 106, pp. 657-667, (1982). Also see S. Shuster, M. Black and E. McVitie, The influence of age and sex on skin thickness, skin collagen and density, British Journal of Dermatology, vol. 93, (1975). See also J. Durnin, and M. Rahaman, The assessment of the amount of fat in the human body from measurements of skin fold thickness, British Journal 30 of Nutrition, vol. 21, (1967).
Additionally, variations in the subject""s physiological state affect the optical properties of tissue layers and compartments over a relatively short period of time. Such variations, for example, may be related to hydration levels, changes in the volume fraction of blood in the tissue, hormonal stimulation, temperature fluctuations and blood hemoglobin levels. The differences in skin thickness and the composition of the different layers produce a confounding effect in the noninvasive prediction of blood analytes.
While these structural and state variations are the largest sources of variation in the measured near-infrared absorbance spectra, they are not indicative of blood analyte concentrations. Instead, they cause significant nonlinear spectral variation that limits the noninvasive measurement of blood analytes through optically based methods. For example, several reported methods of noninvasive glucose measurement develop calibration models that are specific to an individual over a short period of time. See K. Hazen, Glucose determination in biological matrices using near-infrared spectroscopy, Doctoral Dissertation, University of Iowa, (August 1995). Also see M. Robinson, R. Eaton, D. Haaland, G. Koepp, E. Thomas, B. Stallard and P. Robinson, Noninvasive glucose monitoring in diabetic patients: a preliminary evaluation, Clin. Chem, vol. 38/9, pp. 1618-1622, (1992). Also see S. Malin, T. Ruchti, T. Blank, S. Thennadil and S. Monfre, Noninvasive prediction of glucose by near-infrared diffuse reflectance spectroscopy, Clin. Chem, vol. 45:9, pp. 1651-1658, (1999).
A related application, S. Malin, T. Ruchti, An Intelligent System For Noninvasive Blood Analyte Prediction, U.S. patent application Ser. No. 09/359,191; filed Jul. 22, 1999, disclosed an apparatus and procedure for substantially reducing this problem by classifying subjects according to spectral features that are related to the tissue characteristics prior to blood analyte prediction. The extracted features are representative of the actual tissue volume irradiated. The groups or classes are defined on the basis of tissue similarity such that the spectral variation within a class is small compared to the variation between classes. These internally consistent classes are more suitable for multivariate analysis of blood analytes since the largest source of spectral interference is substantially reduced. In this manner, by grouping individuals according to the similarity of spectral characteristics that represents the tissue state and structure, the confounding nonlinear variation described above is reduced and prediction of blood analytes is made more accurate.
The general method of classification relies on the determination of spectral features most indicative of the sampled tissue volume. The magnitude of such features represents an underlying variable, such as the thickness of tissue or level of hydration. It would therefore be highly advantageous to have a non-invasive method of determining skin thickness and characterizing the chemical and structural properties of the various layers.
Skin Thickness Determination
Skin thickness determinations are valuable for several purposes. The thickness of skin tissue and the individual layers provide valuable diagnostic information in a number of circumstances. For example, skin thickness is an important indicator of changes in the skin due to chronological ageing and photo ageing. Skin thickness measurements also provide important information related to a variety of endocrine disorders. Furthermore, a relationship between skin thickness and bone density has been observed. Therefore, skin thickness measurements have potential application in the diagnosis and monitoring of bone loss disorders.
As discussed above, the skin thickness measurement provides information about one of the primary sources of tissue variability and is therefore effective for establishing the general category of the tissue structure. The various categories are suitable for further spectral analysis and calibrations such as blood analyte measurement. Finally, the thickness can be used in conjunction with a diffuse reflectance spectrum for the purpose of path length normalization in spectroscopic examination of the skin.
The most common method of determining the thickness of the skin and its constituent layers is through histological examination of a biopsy specimen. Biopsy has the obvious disadvantage of being an invasive procedure. The subjects must endure an appreciable level of inconvenience and discomfort, and they are exposed to the risks associated with any surgical procedure. It is also a time-consuming, multi-step procedure, requiring skilled medical personnel and multiple pieces of equipment. The ensuing histological examination requires specialized equipment and personnel trained in special laboratory techniques such as tissue sectioning. A simple, non-invasive method of determining skin thickness in vivo would be highly useful.
In fact, a non-invasive method of skin thickness determination using ultrasonography is known [see Tan, et al]. A beam of ultrasound is directed toward a target site. The reflected ultrasound is detected and an image, or sonogram, of the site is generated. Subsequent visual inspection of the resulting image allows an estimation of overall skin thickness. While this method circumvents the obvious disadvantages of biopsy and histological examination, its utility is limited to providing a macroscopic image of the targeted tissue, reflecting the state of the tissue at the time of examination. Ultrasonography cannot provide detailed information concerning the individual tissue layers. It would be desirable to have a quantitative method of skin thickness determination that also allowed the structural and chemical characterization of the individual layers that the skin comprises, and that provided data for further analysis and classification, such as blood analyte prediction.
Disclosed is a novel approach to measuring the overall and layer-by-layer thickness of in vivo skin tissue based on near infrared absorbance spectra. The disclosed methods also yield the chemical composition of the absorbing and/or scattering species of each layer. Finally, a method of path length normalization for the purpose of noninvasive analyte prediction on the basis of skin thickness and layer constituents is disclosed.